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Remote Sensing
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Remote Sensing for Monitoring Infrastructure Deformation
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Remote Sensing for Monitoring Infrastructure Deformation

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".

Deadline for manuscript submissions: closed (15 September 2020) | Viewed by 30064

Special Issue Editors

Prof. Dr. Maria Marsella

E-Mail Website
Guest Editor
Department of Civil, Construction and Environmental Engineering (DICEA), Sapienza University of Rome, Via Eudossiana 18, I-00184 Rome, Italy
Interests: geomatic; DInSAR; laser scanning; photogrammetry; GNSS
Special Issues, Collections and Topics in MDPI journals
Dr. Carla Nardinocchi

E-Mail Website
Guest Editor
Department of Civil, Construction and Environmental Engineering (DICEA), Sapienza University of Rome, Via Eudossiana 18, I-00184 Rome, Italy
Interests: geomatic; laser scanning; photogrammetry; UAV

Special Issue Information

Dear Colleague,

The need for the development of reliable cost-effective systems for monitoring engineering infrastructure is increasing, especially considering the effects of aging and the impact of natural hazards. Monitoring systems capable of detecting and measuring slow structural deformation are based on a variety of technologies, from the ground-based methods (Ground-Based Synthetic Aperture Radar Interferometry (GBInSAR), Terrestrial Laser Scanning (TLS), robotic total station RTS (robotic total stations), and more commonly GNSS (Global Navigation Satellite System) to aerial and satellite data collected from different sensors (e.g., hyperspectral, SAR, LiDAR, UAV, thermal imagery, etc.). Besides, the growing use of UAVs has opened new challenging applications for camera vision systems based on such systems.

The goal of this Special Issue is to gather high-quality original research articles and reviews on current research studying methods and data analysis adopted for infrastructure deformation monitoring.

We would like to invite manuscripts on one of the topics of interest. These include, but are not limited to, the development, validation, and implementation of innovative monitoring techniques as well as processing methods and applications for controlling and managing large civil infrastructure. Moreover, we cordially welcome application papers, including change detection, data fusion/data integration, and technical reviews.

Dr. Maria Marsella
Dr. Carla Nardinocchi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • geomatic monitoring 
  • displacement measurement 
  • deformation analysis 
  • infrastructure 
  • control and maintenance

Published Papers (7 papers)

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Research

23 pages, 21173 KiB  
Article
An Application of Persistent Scatterer Interferometry (PSI) Technique for Infrastructure Monitoring
by Peppe J. V. D’Aranno, Alessandro Di Benedetto, Margherita Fiani, Maria Marsella, Ilaria Moriero and José Antonio Palenzuela Baena
Remote Sens. 2021, 13(6), 1052; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13061052 - 10 Mar 2021
Cited by 24 | Viewed by 3993
Abstract
In the absence of systematic structural monitoring to support adequate maintenance standards, many existing infrastructures may reach unacceptable quality levels during their life cycle, resulting in significant damage and even potential failure. The metropolitan area of the Gulf of Salerno (Italy), served by [...] Read more.
In the absence of systematic structural monitoring to support adequate maintenance standards, many existing infrastructures may reach unacceptable quality levels during their life cycle, resulting in significant damage and even potential failure. The metropolitan area of the Gulf of Salerno (Italy), served by a complex multimodal transport network connecting the port area to the roads and railways surrounding the urban area, represents an important industrial and commercial hub at the local and international scale. This particular scenario, developed in a complex morphological and geological context, has led to the interference and overlapping of the transport network (highway, railway, main and secondary roads) that run through the piedmont area north of the port. Given the relevance of the area, our research aims to highlight the capabilities of the persistent scatterer interferometry (PSI) technique, belonging to the group of differential interferometric synthetic aperture radar (SAR), to extract space–temporal series of displacements on ground points or artifacts with millimeter accuracy useful to understand ongoing deformation processes. By using archived data from the European Space Agency missions, i.e., ERS1/2 (European remote-sensing satellite) and ENVISAT (environmental satellite), and the most recent data from COSMO-SkyMed constellations, it was possible to collect a 28-year dataset that was used to spatially analyze displacement patterns at a site-specific scale to check the stability of viaducts and embankments, and on a larger scale to understand the activity of the surrounding slopes. Despite the different resolution and subsequently the ground density, the analysis of the different datasets showed a spatiotemporal consistency in the displacement patterns that concerned two subareas showing significant annual velocity trends, one northeast of the city and the second in the port area. The analysis presented in this paper highlights how a complex geologic area, combining slope movements and various fault systems, could be a major concern for the stability of the overlying infrastructure and also the role that a PSI analysis can play in remotely monitoring their behavior over long periods of time. Full article
(This article belongs to the Special Issue Remote Sensing for Monitoring Infrastructure Deformation)
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17 pages, 3965 KiB  
Article
DInSAR for Road Infrastructure Monitoring: Case Study Highway Network of Rome Metropolitan (Italy)
by Felipe Orellana, Jose Manuel Delgado Blasco, Michael Foumelis, Peppe J.V. D’Aranno, Maria A. Marsella and Paola Di Mascio
Remote Sens. 2020, 12(22), 3697; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12223697 - 11 Nov 2020
Cited by 25 | Viewed by 4000
Abstract
The road network of metropolitan Rome is determined by a large number of structures located in different geological environments. To maintain security and service conditions, satellite-based monitoring can play a key role, since it can cover large areas by accurately detecting ground displacements [...] Read more.
The road network of metropolitan Rome is determined by a large number of structures located in different geological environments. To maintain security and service conditions, satellite-based monitoring can play a key role, since it can cover large areas by accurately detecting ground displacements due to anthropic activities (underground excavations, interference with other infrastructures, etc.) or natural hazards, mainly connected to the critical hydrogeological events. To investigate the area, two different Differential Interferometry Synthetic Aperture Radar (DInSAR) processing methods were used in this study: the first with open source using the Persistent Scatterers Interferometry (PSI) of SNAP-StaMPS workflow for Sentinel-1 (SNT1) and the second with the SBAS technique for Cosmo-SkyMed (CSK). The results obtained can corroborate the displacement trends due to the characteristics of the soil and the geological environments. With Sentinel-1 data, we were able to obtain the general deformation overview of the overall highways network, followed by a selection and classification of the PSI content for each section. With Cosmo-SkyMed data, we were able to increase the precision in the analysis for one sample infrastructure for which high-resolution data from CSK were available. Both datasets were demonstrated to be valuable for collecting data useful to understand the safety condition of the infrastructure and to support the maintenance actions. Full article
(This article belongs to the Special Issue Remote Sensing for Monitoring Infrastructure Deformation)
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16 pages, 17427 KiB  
Article
PSI Clustering for the Assessment of Underground Infrastructure Deterioration
by Nicola Amoroso, Roberto Cilli, Loredana Bellantuono, Vincenzo Massimi, Alfonso Monaco, Davide Oscar Nitti, Raffaele Nutricato, Sergio Samarelli, Niccolò Taggio, Sabina Tangaro, Andrea Tateo, Luciano Guerriero and Roberto Bellotti
Remote Sens. 2020, 12(22), 3681; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12223681 - 10 Nov 2020
Cited by 6 | Viewed by 2287
Abstract
Remote sensing images find application in several different domains, such as land cover or land usage observation, environmental monitoring, and urbanization. This latter field has recently witnessed an interesting development with the use of remote sensing for infrastructural monitoring. In this work, we [...] Read more.
Remote sensing images find application in several different domains, such as land cover or land usage observation, environmental monitoring, and urbanization. This latter field has recently witnessed an interesting development with the use of remote sensing for infrastructural monitoring. In this work, we present an analysis of Sentinel-1 images, which were used to monitor the Italian provinces of Bologna and Modena located at the Emilia Region Apennines foothill. The goal of this study was the development of a machine learning-based detection system to monitor the deterioration of public aqueduct infrastructures based on Persistent Scatterer Interferometry (PSI). We evaluated the land deformation over a temporal range of five years; these series feed a k-means clustering algorithm to separate the pixels of the region according to different deformation patterns. Furthermore, we defined the critical areas as those areas where different patterns collided or overlapped. The proposed approach provides an informative tool for the structural health monitoring of underground infrastructures. Full article
(This article belongs to the Special Issue Remote Sensing for Monitoring Infrastructure Deformation)
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20 pages, 6027 KiB  
Article
Dynamic Modal Identification of Telecommunication Towers Using Ground Based Radar Interferometry
by Giovanni Nico, Giuseppina Prezioso, Olimpia Masci and Serena Artese
Remote Sens. 2020, 12(7), 1211; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12071211 - 09 Apr 2020
Cited by 11 | Viewed by 3802
Abstract
This work presents a methodology to monitor the dynamic behaviour of tall metallic towers based on ground-based radar interferometry, and apply it to the case of telecommunication towers. Ground-based radar displacement measurements of metallic towers are acquired without installing any Corner Reflector (CR) [...] Read more.
This work presents a methodology to monitor the dynamic behaviour of tall metallic towers based on ground-based radar interferometry, and apply it to the case of telecommunication towers. Ground-based radar displacement measurements of metallic towers are acquired without installing any Corner Reflector (CR) on the structure. Each structural element of the tower is identified based on its range distance with respect to the radar. The interferometric processing of a time series of radar profiles is used to measure the vibration frequencies of each structural element and estimate the amplitude of its oscillation. A methodology is described to visualize the results and provide a useful tool for the real-time analysis of the dynamic behaviour of metallic towers. Full article
(This article belongs to the Special Issue Remote Sensing for Monitoring Infrastructure Deformation)
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25 pages, 12461 KiB  
Article
Mobile Laser Scanning Data for the Evaluation of Pavement Surface Distress
by Maria Rosaria De Blasiis, Alessandro Di Benedetto and Margherita Fiani
Remote Sens. 2020, 12(6), 942; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12060942 - 14 Mar 2020
Cited by 37 | Viewed by 5844
Abstract
The surface conditions of road pavements, including the occurrence and severity of distresses present on the surface, are an important indicator of pavement performance. Periodic monitoring and condition assessment is an essential requirement for the safety of vehicles moving on that road and [...] Read more.
The surface conditions of road pavements, including the occurrence and severity of distresses present on the surface, are an important indicator of pavement performance. Periodic monitoring and condition assessment is an essential requirement for the safety of vehicles moving on that road and the wellbeing of people. The traditional characterization of the different types of distress often involves complex activities, sometimes inefficient and risky, as they interfere with road traffic. The mobile laser systems (MLS) are now widely used to acquire detailed information about the road surface in terms of a three-dimensional point cloud. Despite its increasing use, there are still no standards for the acquisition and processing of the data collected. The aim of our work was to develop a procedure for processing the data acquired by MLS, in order to identify the localized degradations that mostly affect safety. We have studied the data flow and implemented several processing algorithms to identify and quantify a few types of distresses, namely potholes and swells/shoves, starting from very dense point clouds. We have implemented data processing in four steps: (i) editing of the point cloud to extract only the points belonging to the road surface, (ii) determination of the road roughness as deviation in height of every single point of the cloud with respect to the modeled road surface, (iii) segmentation of the distress (iv) computation of the main geometric parameters of the distress in order to classify it by severity levels. The results obtained by the proposed methodology are promising. The procedures implemented have made it possible to correctly segmented and identify the types of distress to be analyzed, in accordance with the on-site inspections. The tests carried out have shown that the choice of the values of some parameters to give as input to the software is not trivial: the choice of some of them is based on considerations related to the nature of the data, for others, it derives from the distress to be segmented. Due to the different possible configurations of the various distresses it is better to choose these parameters according to the boundary conditions and not to impose default values. The test involved a 100-m long urban road segment, the surface of which was measured with an MLS installed on a vehicle that traveled the road at 10 km/h. Full article
(This article belongs to the Special Issue Remote Sensing for Monitoring Infrastructure Deformation)
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29 pages, 15291 KiB  
Article
A Mobile LiDAR for Monitoring Mechanically Stabilized Earth Walls with Textured Precast Concrete Panels
by Mohammed Aldosari, Abdulla Al-Rawabdeh, Darcy Bullock and Ayman Habib
Remote Sens. 2020, 12(2), 306; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12020306 - 17 Jan 2020
Cited by 17 | Viewed by 3501
Abstract
Mechanically Stabilized Earth (MSE) walls retain soil on steep, unstable slopes with crest loads. Over the last decade, they are becoming quite popular due to their high cost-to-benefit ratio, design flexibility, and ease of construction. Like any civil infrastructure, MSE walls need to [...] Read more.
Mechanically Stabilized Earth (MSE) walls retain soil on steep, unstable slopes with crest loads. Over the last decade, they are becoming quite popular due to their high cost-to-benefit ratio, design flexibility, and ease of construction. Like any civil infrastructure, MSE walls need to be continuously monitored according to transportation asset management criteria during and after the construction stage to ensure that their expected serviceability measures are met and to detect design and/or construction issues, which could lead to structural failure. Current approaches for monitoring MSE walls are mostly qualitative (e.g., visual inspection or examination). Besides being time consuming, visual inspection might have inconsistencies due to human subjectivity. This research focuses on a comprehensive strategy using a mobile LiDAR mapping System (MLS) for the acquisition and processing of point clouds covering the MSE wall. The processing strategy delivers a set of global and local performance measure for MSE walls. Moreover, it is also capable of handling MSE walls with smooth or textured panels with the latter being the focus of this research due to its more challenging nature. For this study, an ultra-high-accuracy wheel-based MLS has been developed to efficiently acquire reliable data conducive to the development of the serviceability measures. To illustrate the feasibility of the proposed acquisition/processing strategy, two case studies in this research have been conducted with the first one focusing on the comparative performance of static and mobile LiDAR in terms of the agreement of the derived serviceability measures. The second case study aims at illustrating the feasibility of the proposed strategy in handling large textured MSE walls. Results from both case studies confirm the potential of using MLS for efficient, economic, and reliable monitoring of MSE walls. Full article
(This article belongs to the Special Issue Remote Sensing for Monitoring Infrastructure Deformation)
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19 pages, 14252 KiB  
Article
Damage Detection and Analysis of Urban Bridges Using Terrestrial Laser Scanning (TLS), Ground-Based Microwave Interferometry, and Permanent Scatterer Interferometry Synthetic Aperture Radar (PS-InSAR)
by Xianglei Liu, Peipei Wang, Zhao Lu, Kai Gao, Hui Wang, Chiyu Jiao and Xuedong Zhang
Remote Sens. 2019, 11(5), 580; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11050580 - 09 Mar 2019
Cited by 33 | Viewed by 5002
Abstract
This paper presents a practical framework for urban bridge damage detection and analysis by using three key techniques: terrestrial laser scanning (TLS), ground-based microwave interferometry, and permanent scatterer interferometry synthetic aperture radar (PS-InSAR). The proposed framework was tested on the Beishatan Bridge in [...] Read more.
This paper presents a practical framework for urban bridge damage detection and analysis by using three key techniques: terrestrial laser scanning (TLS), ground-based microwave interferometry, and permanent scatterer interferometry synthetic aperture radar (PS-InSAR). The proposed framework was tested on the Beishatan Bridge in Beijing, China. Firstly, a Digital Surface Model (DSM) of the lower surface of the bridge was constructed based on the point cloud generated by using TLS to obtain the potential damage area. Secondly, the dynamic time-series displacement of the potential damage area was acquired by ground-based microwave interferometry, and the Extreme-Point Symmetric Mode Decomposition (ESMD) method was applied to detect damages by the use of signal decomposition and instantaneous frequency calculation. Lastly, the PS-InSAR technique was applied to obtain the surface deformation around Beishatan Bridge by using COSMO-SkyMed images with a ground resolution of 3 m × 3 m, and finally, we analyzed the causes of bridge damage. The experimental results showed that the proposed framework can effectively obtain the potential damage area of the bridge by the DSM from the point cloud by TLS and further judge whether the bridge was damaged by the ESMD method, based on the time-series displacement data. The results also showed that the subway shield construction may be the reason for damage to Beishatan Bridge. Full article
(This article belongs to the Special Issue Remote Sensing for Monitoring Infrastructure Deformation)
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